Date
|
Topic
|
Reading
|
Assignment
|
8/29 | Gonna rock you like a hurricane! | ||
8/31 | Introduction | none | |
9/2 | Introduction/GOFAI | Read chapter 1. You can skip/skim 1.2 and 1.3. Post to moodle 9/1 forum. | Register for the free Stanford AI class (we may use it as a resource later in the semester). |
9/5 | Classic Search | Chap. 2 For your response, select one real or imaginable agent not discussed in class or in the readings, give a PEAS description of the task environment, and characterize it in terms of the properties listed in Section 2.3.2. | Project 0: Tutorial (due by noon) |
9/7 | Classic Search: DFS, BFS, UCS | Chap. 3-3.4 In your response, include a solution to at least one exercise from the end of the chapter. | |
9/9 | Classic Search: Intro. to Heuristics | Rest of Chap. 3 In your response, include a solution to at least one exercise from the end of the chapter. | |
9/12 | Classic Search: More on A* | none | |
9/14 | Beyond Classic Search/Genetic Algorithms | Chap. 4-4.4 | |
9/16 | More Genetic Algorithms | Rest of Chap. 4, Sections 1--3 of the NEAT paper (you may want to skim the rest). | |
9/19 | Adversarial Search | Read all of Chapter 5. In the response, include the solution to at least on problem | |
9/21 | Adversarial Search (same slides as above) | none | |
9/23 | Adversarial Search | none | |
9/24 | Project 1, Search: due midnight (00:01 on 9/25 is late) | ||
9/26 | Probabilities and Expectations (Review?) | Chapter 13 through end of 13.5 (13.6 is also interesting (Wumpus World is defined in Section 7.2)) | |
9/28 | Utilities | Chapter 14-14.2 | |
9/30 | Utilities and UCT | Read pages 1-4 of this paper. No response is required but we will discuss the paper in class. | |
10/3 | Utilities and MDPs | 16-16.3 | |
10/5 | Project 1 | 17-17.3 | |
10/7 | Utilities and MDPs | none | |
10/8 | Project 2, Adversarial Search: due midnight (00:01 on 8/9 is late) | ||
10/12 | Reinforcement Learning | 21-21.3 | |
10/14 | Reinforcement Learning | none | |
10/17 | Reinforcement Learning | Rest of chapter 21 | |
10/19 | Reinforcement Learning | ||
10/21 | Midterm
| ||
10/24 | Review midterm | ||
10/26 | Probabilistic Reasoning | 14-14.4.1 (skim 14.4) | |
10/28 | Probabilistic Reasoning | ||
10/29 | Project 3, RL: due midnight (00:01 on 10/30 is late) | ||
10/31 | Probabilistic Reasoning/Bayesian Networks | 14.5 (skim 14.7) | |
11/2 | Bayesian Networks | ||
11/4 | Bayesian Networks: Join and Sum Out | ||
11/7 | Bayesian Networks | ||
11/9 | Bayesian Networks and Actions Pratice Problem | ||
11/11 | Probabilistic Reasoning over Time | 15.5, 15.6 (15.4 optional) | |
11/14 | Particle Filters | Skim 15-15.3 (reading response not required) | |
11/16 | DBNs/Classification | ||
11/18 | Perceptrons/Neural Networks + Slides from Mitchell | 18-18.2, 18.7 (no reading response) | |
11/28 | Guest Lecture | Project 4, Tracking: due at 11:59pm | |
11/30 | Classical Planning | Respond to chapter 10-10.3 (Skim rest of chapter) | |
12/2 | Classical Planning | ||
12/5 | Guest Lecture | Respond to chapters 26 and 27 | |
12/7 | Ethics/Philosophy | ||
12/9 | Wrap-up | Extra Optional Project: due at 11:59pm (but not counted as late until 12/14 at 11:59pm) | |
12/14 | Final: 8-11am
| Optional papers: 1 2 Potentially useful for studying: 2, 3, 4, 5 1, 2, 5, 6, 7 1, 2, 4, 5, 6 2, 3, 4, 5 (Note: Some have solutions on webpage.) Additional problems: 15.15, 15.16, 10.2, 10.3, 10.4, 10.5, 10.6 |